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Courant Institute of Mathematical Sciences, Scientific Computing and Uncertainty Quantification -CADMOS Chair, New York University
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Inertia in Dirac-Frenkel dynamics significantly enhances parameter evolution stability, making it a game-changer for training complex models like neural networks.
FTM achieves accurate ensemble predictions of chaotic systems at a fraction of the computational cost, revolutionizing how we model stochastic dynamics.
